Check out MIT's Human-Machine Hybrid for Cybersecurity

A group of MIT researchers has sketched out a way to address a gap in cybersecurity that exists between human and machine. Human-made rules, which are meant to alert the system of an attack, don’t work unless an attack exactly matches one of those rules. Machine-learning measures typically rely on anomaly detection. Consequently, false alarms aren’t uncommon and the system starts to distrust itself. Combine these two forces – man and machine – and that’s when magic can happen, according to a group of researchers out of MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). In a paper they published, they suggest a new method to detect cyberattacks using artificial intelligence with constant input from security experts. According their testing, this process can pinpoint 85 percent of cyberattacks and cut…